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Climate-related distribution shifts for marine species are, in general, amplified in northern latitudes. The objective of this study was to predict future distributions of commercially important species in the eastern Bering Sea under six climate scenarios, by incorporating predictions of future oceanographic conditions. We used species distribution modelling to determine potential distribution changes in four time periods (2013–2017, 2030–2039, 2060–2069, and 2090-2099) relative to 1982–2012 for 16 marine fish and invertebrates. Most species were predicted to have significant shifts in the centre of gravity of the predicted abundance, the area occupied, and the proportion of the predicted abundance found in the standard bottom trawl survey area. On average the shifts were modest, averaging 35.2 km (ranging from 1 to 202 km). There were significant differences in the predicted trend for distribution metrics among climate scenarios, with the most extensive changes in distribution resulting from Representative Concentration Pathway 8.5 climate scenarios. The variability in distributional shifts among years and climate scenarios was high, although the magnitudes were low. This study provides a basis for understanding where fish populations might expand or contract in future years. This will provide managers’ information that can help guide appropriate actions under warming conditions.

Deep-water larval fish and zooplankton utilize structurally complex, cold-water coral and sponge (CWCS) habitats as refuges, nurseries and feeding grounds. Fine-scale sampling of these habitats for larval fish and zooplankton has proven difficult. This study implemented a newly designed, autonomous, noninvasive plankton pump sampler that collected large mesozooplankton within 1 m of the seafloor. It was successfully deployed in the western Gulf of Alaska between the Shumagin Islands (~158°W) and Samalga Pass (−170°W), and collected in situ zooplankton from diverse benthic communities (coral, sponge and bare substrates) at depths in excess of 100 m. Key design parameters of the plankton pump were its ability to be deployed from ships of opportunity, be untethered from the vessel during sampling and be deployed and retrieved in high-relief, rocky areas where CWCS are typically present. The plankton pump remains stationary while collecting from the water column, rests within 1 m of the seafloor and captures images of the surrounding habitat and substrate. This plankton pump design is a low-cost, highly portable solution for assessing the role of benthic habitat in the life cycle of mesozooplankton, a linkage that has been relatively underexplored due to the difficulty in obtaining near-bottom samples.

Spatial management of vulnerable benthic ecosystem components such as deep-sea corals and sponges requires adequate maps of their distribution. These maps are often based on statistical models of survey data. The objective of this project was to validate the predictions of existing presence or absence and abundance models of deep-sea corals and sponges in the Aleutian Islands that were based on bottom trawl survey data. Model validation was conducted by comparing bottom trawl survey model predictions to the observations of an in situ camera survey conducted at randomly selected locations. The measures of goodness of fit (area-under-the-receiver-operator-curve, AUC) for the bottom trawl survey model predictions of camera survey observations ranged from 0.59 to 0.77 (for sponges and coral, respectively) and indicated that the bottom trawl survey models predicted the probability of presence for corals accurately across the Aleutian Islands. The bottom trawl survey models explained as little as 3% of the variability in Stylasteridae density and up to 17% of the variability in coral density. These results indicate that models of deep-sea coral distributions based on presence and absence data from bottom trawl surveys can be accurate and can provide useful information for spatial management of these vulnerable taxa. However, for some other taxa, such as sponges, care should be taken interpreting the results of bottom trawl survey models. An interesting finding of this study was that the residuals from the bottom trawl survey model-camera density relationships were negative in areas that remained open to fishing after 2005, possibly indicating an effect of continued bottom trawling on the abundance of corals in these areas. This study highlights the importance of validating models of species distribution using independent surveys, so that the results can be used with confidence to support decision-making processes.

Euphausiids (principally Thysanoessa spp.) are found in high abundance in both the eastern Bering Sea (EBS) and the Gulf of Alaska (GOA). They are an important part of these cold-water coastal and pelagic ecosystems as a key prey item for many species, including marine mammals, seabirds, and fish, forming an ecological link between primary production and higher trophic levels. Acoustic-trawl (AT) survey methods provide a means of monitoring euphausiid abundance and distribution over a large spatial scale. Four years of AT and bottom-trawl survey data (2003, 2005, 2011, and 2013) were available from consistently sampled areas around Kodiak Island, including Shelikof Strait, Barnabas Trough, and Chiniak Trough. We identified euphausiid backscatter using relative frequency response and targeted trawling, and created an annual index of abundance for euphausiids. This index has broad application, including use in the stock assessments for GOA walleye pollock (Gadus chalcogrammus) and other species, as an ecosystem indicator, and to inform ecological research. We then used generalized additive models (GAMs) to examine the relationship between relative euphausiid abundance and potential predictors, including pollock abundance, temperature, bottom depth, and primary production. Model results were compared with an updated GAM of euphausiid abundance from the EBS to determine if the factors driving abundance and distribution were consistent between both systems. Temperature was not a strong predictor of euphausiid abundance in the GOA as in the EBS; warmer temperatures and lack of seasonal ice cover in the GOA may be a key difference between these ecosystems. Pollock abundance was significant in both the GOA and the EBS models, but was not a strongly negative predictor of euphausiid abundance in either system, a result not consistent with top-down control of euphausiid abundance.